Due to the number of mobile phones and similar devices in use, particularly in developed countries, users can be connected to the World Wide Web (WWW) from almost anywhere in the globe. Among the advantages that this brings, the ability to locate and identify a specific user's location is one of the most helpful. An example technology used for locating users is the global positioning system (GPS), which can be used to determine a current geographical location of a user device. This location determination may be used for purposes such as, for example, navigation and emergency rescue services. To this end, accurate identification of a user's current location is particularly important.
Specifically, when a person faces an emergency and calls an emergency services phone number, he or she is asked by an emergency dispatcher to provide an address in order to assist the dispatcher in locating the scene of the emergency. However, the address may be unknown to the person, or the person may otherwise be unable to provide the address. In such instances, a GPS on the person's mobile device may be utilized by the dispatcher to locate the person and render emergency aid.
Existing solutions for location identification provide various methods for estimating locations of mobile devices in open and closed environments. Many of these solutions are executed using location pointers of the user's estimated location that are displayed on maps such as, for example, virtual maps, graphical maps, metric maps, and the like. Some indoor positioning systems use preconfigured maps that include visual characteristics of a certain location such as an apartment, a building complex, etc. Other indoor positioning systems generate maps using signals that are transmitted by a user device associated with a user while the user walks through a location.
The existing solutions for location identification can be inaccurate, especially when used for indoor navigation. More specifically, these existing solutions may not be able to precisely determine a location within a building, and may face further challenges in determining altitude/height within a building. Further, existing solutions cannot identify precise indoor locations such as floors, rooms, or addresses within a building (e.g., an apartment number or address). Such precise indoor locations may be critical in densely populated areas, where emergency services cannot efficiently respond without knowing the target location within a building.
It would therefore be advantageous to provide a solution that would overcome the challenges noted above.